Isolation monitoring device and method

ABSTRACT

Wide deployment of high voltage battery systems in traction, industrial and renewable energy installations is raising the concerns for human safety. Exposure to hazardous high voltages may occur due to deterioration of insulation materials or by accidental events. It is thus important to monitor for such faults and being able to provide timely warnings to affected persons. For this purpose it has become mandatory for electrified passenger vehicles (CFR 571.305) to maintain high isolation values which can be continuously monitored by electrical isolation monitoring devices. The task of monitoring isolation resistance within the electrically noisy car environment is not a trivial task and the solution to this problem has become quickly a field of research and innovation for all affected industries.

BACKGROUND OF THE INVENTION

Wide deployment of high voltage battery systems in traction, industrialand renewable energy installations is raising the concerns for humansafety. Exposure to hazardous high voltages may occur due todeterioration of insulation materials or by accidental events. It isthus important to monitor for such faults and being able to providetimely warnings to affected persons. For this purpose it has becomemandatory for electrified passenger vehicles (CFR 571.305) to maintainhigh isolation values which can be continuously monitored by electricalisolation monitoring devices. The task of monitoring isolationresistance within the electrically noisy car environment is not atrivial task and the solution to this problem has become quickly a fieldof research and innovation for all affected industries.

The function of the isolation monitoring device is to determine thevalue of the isolation resistance between either of the batteryterminals and the chassis. Furthermore it must issue an alarm if theisolation resistance becomes lower than a certain value. This value isdetermined by the human body tolerance to electrical current. The tableof FIG. 1 shows typical human body reaction to current passing throughthe body. The resistance values shown for the different paths in thehuman body are typical and can vary widely based on the condition of theskin and other factors. Nevertheless, one may notice that the order ofmagnitude of resistances is relatively small.

When an electrical system is not connected to the Earth, as in the caseof an electrical vehicle, the system is said to have a “floating”ground. The abbreviation IT comes from the French term “isolé terre”(isolated earth) and it is used by IEC (International ElectrotechnicalCommission) to describe a power system with “floating” ground. FIG. 2shows such a system as it is implemented in an electrified vehicle.

In this system, the high voltage battery and all the car systemsconnected to it are isolated from the Chassis ground which consists ofthe metal body of the car that passengers come in constant contact with.The battery of an electric vehicle is connected through DC to ACconverters to motors, generators, which are typically the same motorsacting as generators when the car is decelerating or moving downhill,and the various car auxiliary systems through DC to DC converters. Thetwo capacitors shown on the right represent either capacitors placedwith the purpose of reducing EMI (electromagnetic interference) noise orthe small parasitic capacitances that exist in any electrical system.

This type of grounding serves an important purpose for the safety of acar and those in contact with it. If for example the negative of thebattery was connected to the Chassis, and an isolation fault occurred toone of the positive cables, an immediate short would be created at thebattery terminals causing fuses to blow. This could result in immediateloss of power in the electric vehicle—including loss of brakingpower—which could result in accidents or other problems.

In contrast, in an IT power system as shown in FIG. 3, a singleisolation fault 340 would not cause an immediate power failure. It alsowould not cause any danger for the car passengers, as long as they don'ttouch the unaffected terminal which is shielded from passenger access.Instead the driver will receive a warning and will then be able to drivethe car safely and in full capacity to a service location. In case of anaccident, which may cause itself an isolation fault, the emergency firstresponders will be warned to take safety precautions and to avoidtouching affected parts of the automobile.

An isolation fault may also occur through excessive deterioration ofinsulating materials resulting from extreme hot-cold cycles, by sparksand other electrical hazards or even by rodents.

To address these potential risks, the National Highway Traffic SafetyAdministration (NHTSA) of the Department of Transportation (DOT) issueda final rule amending the electrical shock protection requirements ofFederal Motor Vehicle Safety Standard No. 305 (49 CFR 571.305), whichmandates for a DC voltage system a minimum number of ohms/volt ofisolation of a high voltage source. In essence it specifies the maximumcurrent that can pass through the isolation resistance path, whichcannot be more than 2 mA without an isolation monitoring device (500ohm/volt) or 10 mA with one (100 ohm/volt). As an example, for a DCvoltage source of 400 volts with isolation monitoring, the specificationis 100 ohm/volt. This translates into a minimum isolation resistance of40 kilohms. Without isolation monitoring the minimum value for the samesystem would be 200 kilohms.

The difference between the allowed values of ohms/volt depending onwhether an isolation monitoring device is present can be appreciated byunderstanding the absence of one. If there is no isolation monitoringdevice, the isolation resistance can be measured only during scheduledservice of the vehicle. The only method the vehicle manufacturer has toensure conformance in this case is by using highly rated materials andwiring protection and hoping that isolation faults will only happengradually and will be discovered during scheduled inspections. Anisolation monitoring device, in contrast, operates all of the timemaking it the preferred method for future vehicle builds.

One can see the impact of these specifications by looking again at FIG.3. The isolation fault 340 would be the isolation resistance (40 kilohmor 200 kilohm). The connection 315 would be the resistance path of ahuman body touching the other terminal. There would be a closedelectrical circuit through the battery and the chassis with theisolation resistance dominating the current value as it is much higherthan the human body resistance. At the limit of 40 kilohms, the persontouching the positive terminal would still be safe albeit lightlyshocked.

Together with establishing these requirements, the CFR 571.305 safetystandard specifies a method for calculating the isolation resistance.Referred to as the “voltage” method and prescribed for use in vehicleservice stations, the method will be described in more detail below.Some improvements to this “voltage” method also exist, about which morewill be said below.

The “Voltage” Method

In the drawings of FIG. 5 the resistances 550 and 560 represent theisolation resistances between the negative and the positive batteryterminals to the chassis. Two voltmeters measure the correspondingvoltages U1 and U2. If there is a difference on the readings, a knownresistance 570 is connected to the side with the higher voltage readingand using Ohm's law the smaller isolation resistance is calculated. Thismethod is referred to as the “voltage” method and it is prescribed foruse in vehicle service stations. Although simple and straightforward themethod has serious drawbacks that limit its efficiency when usedcontinuously in an operating vehicle.

First, the insertion of a resistance in the isolation path may adverselyaffect the isolation of the IT system. This is because resistor 570cannot have an arbitrarily high value as the method relies on its effectupon the measured voltage. The measurement method itself may jeopardizeisolation. Also, switching loads on and off in a high voltage systemrequires expensive components. The measurement assumes that the batteryvoltage remains constant during successive measurements. In an operatingvehicle this condition is rarely true (less than 20% of operating time).

U.S. Pat. No. 9,322,867 presents a variation of the method whichovercomes the issue of the negative impact of resistor 570 by usinginstead different types of current limiting devices. The issues of highcost of high voltage switching and the battery noise impact still remainunaddressed.

The “Pulse” Method

The pulse method is overcoming some of the problems associated with the“voltage” method by injecting a pulse into the DC network as shown inFIG. 6.

Variations of this method are well known and referenced at EP 0 654 673B1, EP 1 586 910 B1 and DE 101 06 200 C1. The main shortcomings of thismethod are:

-   -   The accuracy of the method is susceptible to disturbances on the        DC lines which typically occur when the vehicle or system is        operating.    -   As a result a large number of measurements have to be taken        until reliable values are obtained.

The “Frequency” Method

A variation of the “pulse” method is the “frequency” injection method(U.S. Pat. No. 5,450,328, U.S. Pat. No. 9,069,025 B2). In this method anAC signal of known frequency is injected or superimposed on the DCpulse. Through band-pass and low-pass filtering of the resulting signal,the values of impedance and resistance are estimated using digitalsignal processing techniques.

The method requires digital signal processing capabilities for digitalfilter implementation as well as the DFT/FFT processing of the monitoredresponses. The accuracy also is affected by dynamic changes in the loadand achieves an acceptable level of accuracy when load changes aresmall.

Characteristics of a “Good” Isolation Monitoring Device

-   -   Based on the analysis of the issues with prior art, it is        desirable for an isolation monitoring method to possess the        following characteristics:    -   The method should not introduce isolation hazards during        measurement; neither should it drain significantly the battery        during continuous operation.    -   It should provide information not only for the isolation        resistance but also for the isolation capacitance which can also        become hazardous under certain conditions.    -   The method should be accurate not only in periods of system        inactivity but under all operating conditions    -   The method should not produce “false alarms”.    -   It should be fast and continuously updated. Ideally it should be        able to detect intermittent isolation faults.

The Method According to the Invention

The methods described so far are deterministic relying on a unique knowninput (pulse, frequency, etc.) to produce an output that can uniquelyidentify the unknown parameters of resistance and capacitance. Thesemethods are simple but fail in most instances when the varying powerload signal interferes.

Using the Power Load Signal as Excitation Source

It is beneficial for safety to be able to accurately determine theisolation resistance and capacitance when the power system is active. Inthe case of an electrified vehicle this would correspond to 80% of thetime the vehicle is in use.

The disclosed method uses these widely varying load signals thatnaturally occur in an IT power system to identify the isolationparameters. As a result, accurate information on the isolation conditioncan be derived most of the time the system is operational. An auxiliaryexcitation signal is used in periods of system inactivity in order toensure 100% monitoring availability.

Method to Estimate the Element Values of the Isolation Path

According to this method, a model is used to represent the IT powersystem along with the isolation resistances and capacitances between theIT power system and the chassis ground. The objective is to determinethe values of the unknown resistive and capacitive isolation pathsbetween the IT power system and the chassis ground. As shown in FIG. 6Aand FIG. 6B those isolation paths can be modeled as parallel RCcircuits. Below, we will denote R₁ and C_(Y1) the resistor andcapacitors in the RC circuit for the isolation path on the negative sideof the battery, and R₂ and C_(Y2) those for the isolation path on thepositive side of the battery.

The method of determining the values of R₁, R₂, C_(Y1) and C_(Y2)comprises:

-   -   Measuring a first value of voltages U₁ and U₂ associated with        the isolation path between the IT system and the ground chassis    -   Measuring a second value of voltages U_(1′) and U₂′ associated        with the isolation paths between the IT power system and the        ground chassis    -   Estimating the values for the model resistors R₁, R₂ and        capacitors C_(Y1) and C_(Y2) associated with the measurements        U₁, U₂, U₁′ and U₂′ through a function that minimizes the        discrepancy between the measurements and a theoretical model for        the RC circuits describing the isolation paths    -   Accepting the estimated values of each of R₁, R₂, C_(Y1) and        C_(Y2) of the isolation circuit model as the present value        estimate and storing it in a storage medium.

It should be appreciated that this method can utilize the varyingvoltage of the IT power system as the measurement signal for performingthe calculations. If the voltage of the IT power system is idle avoltage signal source can be used instead.

The function of minimizing the deviation between the voltagemeasurements and the theoretical model for the RC circuits describingthe isolation paths can be a least-square error estimate performed overa predetermined number of voltage measurements.

An improvement on the method can be achieved by utilizing a stochasticfilter, such as a Kalman filter, to minimize the measurement and modelnoise.

The combined method consists of two steps:

1. at first, a fixed number of measurements for the voltages at thebattery terminals and the excitation voltage are collected and used asinputs for a least-square estimator which produces estimates of theisolation parameters (i.e., leakage resistors and leakage capacitors)together with uncertainties for those estimates,

2. the next step is a filtering step implemented using a Kalman filterand designed to maintain the most likely values for the isolationparameters with associated uncertainties by using the results of theleast-square estimator in time.

More details on those two steps are given below.

Isolation Parameters Prediction Using a Least-Square Estimator

During operation of the monitoring system, measurements are collectedfor the values of the voltages at the battery terminals and of theexcitation voltage. The purpose of the least-square estimator is tominimize the discrepancy between the measurements and a theoreticalmodel for the isolation paths modeled as RC circuits, the latterexpressing the conservation of charge in the monitoring circuit. Theleast-square estimator therefore receives as inputs a buffer containinga fixed number of the aforementioned voltage measurements and producesas outputs predictions for the isolation parameters, together withuncertainties for those predictions. The predictions are expressed as avector whose components represent the isolation parameters, and theuncertainties are expressed as a covariance matrix for this vector. Itfollows that, as the monitoring system is operated, the least-squareestimator can be used at any time to provide a prediction of the currentisolation parameters vector and the associated uncertainties. In theproposed method, the estimator is used to regularly produce newpredictions and uncertainties which are then passed on to the filterdescribed below. The number of voltage measurements as inputs for theleast-square estimator can be predetermined or adjusted dynamicallydepending on the conditions of operation.

Filtering of Predictions for Isolation Parameters Using a Kalman Filter

It follows from the previous section that the monitoring device uses theleast-square estimator to obtain predictions and uncertainties for theisolation parameters as a function of time. That is, as the monitoringdevice is operated, time series of predictions and uncertainties aregenerated by the least-square estimator. Those time series can be seenas a stochastic process in itself since the measured data sent to theleast-square estimator are themselves originating from a stochasticprocess. Therefore, the purpose of the filter is to maintain estimatesfor the most likely values for the isolation parameters vector and theassociated uncertainties. This is achieved by using a Kalman filterimplementation in which the results from the least-square estimator areassimilated to noisy measurements of the isolation parameters. Thefilter receives as inputs the previous estimates for the most likelyvalues of the isolation parameters and the associated uncertainties, andpredictions from the least square estimator. The outputs are newestimates for most likely values of the isolation parameters and theassociated uncertainties.

Experimental Results

Experimental results are provided in FIGS. 12-16 based on the apparatusshown in FIG. 8B to FIG. 10 and FIG. 17. The load profile used was basedon city driving data measured on a BMW i3 model. The load profile wasaccelerated 4 times in order to test the algorithms in more adverse loadconditions. Measured data along with the produced estimates are providedin FIGS. 12-16.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagram of electrical current paths through a human bodyand each path's approximate value of resistance.

FIG. 1B is a table of biological effects upon the human body ofelectrical currents.

FIG. 2 illustrates an IT grounding system of an electric vehicle.

FIG. 3 illustrates an IT grounding system with a single isolation fault.

FIG. 4 illustrates an IT grounding system of an electric vehicleutilizing an Isolation Monitoring device.

FIGS. 5A-5C show the “voltage method” for determining isolationresistance.

FIGS. 6A-6C show the “pulse method” improvement of injecting pulses intothe DC network.

FIG. 7 shows superposition of an injected AC signal on a DC pulse in anetwork according to the “frequency method.”

FIG. 8A shows the variation of battery voltage possible during operationof an electric vehicle.

FIG. 8B shows a model as used to represent the IT power system alongwith the isolation resistances and capacitances between the IT powersystem and the chassis ground.

FIG. 9 shows a least-squared error method used to minimize the errorbetween model predicted values of the isolation path and measurements.

FIG. 10 is a schematic representation of the two-step process toestimate the isolation parameters and associated uncertainties.

FIG. 11 shows a typical Kalman Filter implementation.

FIG. 12 is a plot of example results for the identification of isolationparameters according to the invention.

FIG. 13 is a plot of voltage waveforms at the two battery terminals in adevice under test.

FIG. 14 shows an estimation of the isolation resistance between thepositive terminal and chassis.

FIG. 15 shows an estimation of the isolation resistance between thenegative terminal and chassis.

FIG. 16 displays the application of a Kalman filter on initially noisydata in providing the estimate of isolation resistance.

FIG. 17 is a block diagram of an isolation monitoring device asimplemented in hardware.

DETAILED DESCRIPTION OF THE DRAWINGS

When a human body contacts two points of non-identical electricalpotential, an electric current may flow through the path between thepoints. Approximate values for each of these paths through the humanbody are shown in FIG. 1A and the table in FIG. 1B shows typicalreactions in the human body for given amounts of electric current.

A high voltage battery system 200 with a “floating ground” is shown inFIG. 2. Connected to the battery 201 and insulated from the chassisground 202 are motors 205, 215 and 225. Generators 210 and auxiliarysystems 220 are also connected to the battery 201 and insulated from thechassis ground 202. Actual capacitors and modeled capacitances 230 and240 are either placed or may exist between terminals of the battery 201and the chassis ground 202.

FIG. 3 shows a similar high voltage battery system 300 in which thepositive terminal 310 of the battery 301 is connected via path 315 tothe chassis 302. If an isolation fault 340 was to occur between thenegative terminal 305 and the chassis 302, a short would be createdbetween the battery terminals, causing fuses to blow and affectingvehicle safety.

An isolation monitoring system alerts the operator and responders tohazardous conditions that develop in an electrical system. FIG. 4 showsa high voltage battery system 400 containing an isolation monitoringdevice 440 according to the invention. The device 440 monitors theisolation resistance between the terminals 405 and 410 of the battery401 and the chassis ground 402, and provides warnings of dangerousfaults within the system during vehicle operation.

FIGS. 5A-5C illustrate an implementation of the “voltage” method in ahigh voltage battery system. In FIG. 5A, a battery 501 is isolated fromthe chassis ground 502. Resistances 550 and 560 represent the isolationresistances between the negative 515 and the positive 525 batteryterminals to the chassis 502. Two voltmeters 555 and 565 measure thecorresponding voltages u₁ and u₂. If there is a difference on thereadings, a known resistance 570 is connected to the side with thehigher voltage reading and, using Ohm's law, the smaller isolationresistance is calculated. The method is illustrated in FIGS. 5B and 5Cfor either the case of u₂>u₁ or u₁>u₂, respectively.

An improvement over the “voltage” method, known as the “pulse” method,is shown in FIG. 6A-6C. FIG. 6A shows a DC network. In FIG. 6B, a pulseis injected into the DC network of FIG. 6A. The impedance is thendetermined by monitoring the response over time, as shown in FIG. 6C.

A variation of the “pulse” method, called the “frequency” injectionmethod also exists. In this method, an AC signal of known frequency isinjected or superimposed on the DC pulse. FIG. 7 illustratessuperposition of DC and AC pulse injection on the network. Throughband-pass and low-pass filtering of the resulting signal, the values ofimpedance and resistance are estimated using digital signal processingtechniques.

FIG. 8A shows an example of widely varying battery voltage levels duringoperation of a Hybrid electric vehicle. The graph of FIG. 8A plotsbattery voltage over time under different load conditions. FIG. 8B is anillustration of a model used to represent the IT power system along withthe isolation resistances and capacitances between the IT power systemand the chassis ground.

An exemplary step of minimizing the deviation between measured andestimated values using a least-square estimator is shown in FIG. 9. Inthe figure, a predetermined number of voltage measurements 910 and amodel for the isolation paths modeled as RC circuits 920 are enteredinto a least-square estimator 930. The least-square estimator functionproduces output predictions 950 for the isolation parameters values anduncertainties.

As shown in FIG. 10, output predictions 950 from the least-squareestimator are used as inputs to a stochastic filter 1071. The stochasticfilter 1071 may be, for example, a Kalman filter. The stochastic filter1071 also receives as inputs best estimates 1060 for isolationparameters and uncertainties. Through its operation, the stochasticfilter 1071 outputs new best estimates 1061 for isolation parameters anduncertainties. A second iteration of the stochastic filter 1072 receivesupdated output predictions 951 from the least-square estimator togetherwith best estimates 1061 for isolation parameters and uncertainties.This second operation of the stochastic filter 1072 outputs new bestestimates 1062 for isolation parameters and uncertainties. A detail oftypical Kalman filter operation is shown in FIG. 11.

A graph of example results of the best estimate for the most likelyvalue of capacitor C_(Y1) in the monitoring circuit is shown in FIG. 12.The best estimate is plotted as curve 1210 between curves 1205 and 1215,which themselves represent the narrowing confidence interval for theestimated value due to filtering. The unfiltered, noisy predictions fromthe least-square estimator are shown in the background as the widelyvarying curve 1220.

Voltage waveforms at the two battery terminals of the apparatus of FIG.8B under test are shown in FIG. 13. Estimation of the isolationresistance between the positive terminal and the chassis is plotted inthe graph of FIG. 14. Similarly, estimation of isolation resistancebetween the negative terminal and the chassis is plotted in the graph ofFIG. 15. Both FIG. 14 and FIG. 15 show the method prediction as well asthe method confidence interval under a varying load profile for a givenperiod of time. The estimate of isolation resistance provided by aKalman filter is shown together with the raw results of theleast-squared algorithm in FIG. 16.

A block diagram for the Isolation Measurement Device implemented inhardware is illustrated in FIG. 17.

What has been described is a method to estimate a change in values ofisolation impedance in an isolated ground (IT) electrical systemcomprising a power source, the method comprising: modeling a firstisolation path between a first reference point and a second referencepoint and modeling a second isolation path between a third referencepoint and a fourth reference point, thereby creating a theoretical modelof the isolated ground electrical system; providing an initial value ofa first isolation resistance for the first isolation path and an initialvalue of a second isolation resistance for the second isolation path;measuring an initial value of a voltage between the first referencepoint and the second reference point and storing the measured initialvalue in a storage medium; measuring an initial value of a voltagebetween the third reference point and the fourth reference point andstoring the measured initial value in the storage medium; measuring asubsequent different value of the voltage between the first referencepoint and the second reference point and storing the measured subsequentvalue in the storage medium; measuring a subsequent value of the voltagebetween the third reference point and the fourth reference point andstoring the measured subsequent value in the storage medium; enteringthe measured initial values of the voltages, the measured subsequentvalues of the voltages, the provided values of the isolation impedancesand an elapsed amount of time between the initial measurements and thesubsequent measurements into a mathematical function stored in thestorage medium; wherein the mathematical function minimizes thediscrepancy between the measured change in values of the voltages andthe modeled theoretical values by adjusting values of modeled isolationimpedances associated with the isolation paths in the electrical system;extracting estimated values of isolation impedances associated with theisolation paths in the electrical system by application of themathematical function; and storing the estimated values in the storagemedium.

Also described is an apparatus for estimating a change in values orunknown values of isolation impedance in an isolated ground (IT)electrical power system, comprising: a power source having a positiveterminal and a negative terminal, said terminals connected in circuit toat least one additional electrical component and isolated from a chassisground within the electrical system;

wherein the electrical system contains an isolation impedance betweeneach of the terminals and the chassis ground; a storage medium; meansmeasuring an initial value and a subsequent different value of a voltagebetween the chassis ground and a first reference point and between asecond reference point and a third reference point in the electricalsystem; means storing the measured initial values and the subsequentdifferent values in the storage medium; a mathematical function storedin the storage medium, whereby application of the mathematical functionextracts estimated values of isolation impedances associated with thevoltage measurements by using a model of the electrical system andminimizing an error function.

Also described is a method to estimate unknown values of isolationimpedance in an isolated ground (IT) electrical system comprising apower source and a load, the method comprising: modeling a firstisolation path between a first reference point and a second referencepoint and modeling a second isolation path between a third referencepoint and a fourth reference point, thereby creating a theoretical modelof the isolated ground electrical system; at a time when power from thepower source is being dissipated in the load, measuring an initial valueof a voltage between the first reference point and the second referencepoint and storing the measured initial value in a storage medium; at atime when power from the power source is being dissipated in the load,measuring an initial value of a voltage between the third referencepoint and the fourth reference point and storing the measured initialvalue in the storage medium; at a time when power from the power sourceis being dissipated in the load, measuring a subsequent different valueof the voltage between the first reference point and the secondreference point and storing the measured subsequent value in the storagemedium; at a time when power from the power source is being dissipatedin the load, measuring a subsequent value of the voltage between thethird reference point and the fourth reference point and storing themeasured subsequent value in the storage medium; entering the measuredinitial values of the voltages, the measured subsequent values of thevoltages and an elapsed amount of time between the initial measurementsand the subsequent measurements into a mathematical function stored inthe storage medium; wherein the mathematical function minimizes thediscrepancy between the measured initial values of the voltages, themeasured subsequent values of the voltages, and the modeled theoreticalvalues by adjusting values of modeled isolation impedances associatedwith the isolation paths in the electrical system; extracting estimatedvalues of isolation impedance associated with the isolation paths in theelectrical system by application of the mathematical function;identifying a minimum resistance path from the estimated values ofisolation resistance; and storing the estimated values in the storagemedium.

It will be appreciated that one skilled in the art of isolated groundelectrical systems, varying output power sources and electrical systemscould devise additional obvious improvements and variations upon theinvention described and claimed herein. All such obvious improvementsand variants are intended to be encompassed by the claims which follow.

1. A method to estimate a change in values of isolation impedance in anisolated ground (IT) electrical system comprising a power source, themethod comprising: modeling a first isolation path between a firstreference point and a second reference point and modeling a secondisolation path between a third reference point and a fourth referencepoint, thereby creating a theoretical model of the isolated groundelectrical system; providing an initial value of a first isolationresistance for the first isolation path and an initial value of a secondisolation resistance for the second isolation path; measuring an initialvalue of a voltage between the first reference point and the secondreference point and storing the measured initial value in a storagemedium; measuring an initial value of a voltage between the thirdreference point and the fourth reference point and storing the measuredinitial value in the storage medium; measuring a subsequent differentvalue of the voltage between the first reference point and the secondreference point and storing the measured subsequent value in the storagemedium; measuring a subsequent value of the voltage between the thirdreference point and the fourth reference point and storing the measuredsubsequent value in the storage medium; entering the measured initialvalues of the voltages, the measured subsequent values of the voltages,the provided values of the isolation impedances and an elapsed amount oftime between the initial measurements and the subsequent measurementsinto a mathematical function stored in the storage medium; wherein themathematical function minimizes the discrepancy between the measuredchange in values of the voltages and the modeled theoretical values byadjusting values of modeled isolation impedances associated with theisolation paths in the electrical system; extracting estimated values ofisolation impedances associated with the isolation paths in theelectrical system by application of the mathematical function; andstoring the estimated values in the storage medium.
 2. The method ofclaim 1, wherein the second reference point is a chassis ground of theelectrical system.
 3. The method of claim 2, wherein the fourthreference point is the chassis ground of the electrical system.
 4. Themethod of claim 1, further comprising: comparing the estimated values ofisolation resistance with a range of acceptable values and communicatingthat the estimated value of resistance for an isolation path is outsidethe range of acceptable values.
 5. The method of claim 1, furthercomprising: communicating an amount of estimated energy stored in theisolation impedances.
 6. The method of claim 1, wherein the power sourceis a battery and wherein the first reference point and the thirdreference point are positive and negative terminals of the battery. 7.The method of claim 1, wherein the power source is a supercapacitor. 8.The method of claim 1, wherein the power source is a DC charger.
 9. Themethod of claim 1, further comprising: identifying a minimum resistancepath from the estimated values of isolation resistance.
 10. The methodof claim 9, further comprising: communicating a value of resistance forthe minimum resistance path in the electrical system.
 11. The method ofclaim 9, further comprising: associating the minimum resistance pathwith one of the power source terminals.
 12. The method of claim 1,wherein the theoretical model of the electrical system is an equivalentcircuit model.
 13. The method of claim 1, further comprising: extractingan estimated value of at least a first capacitance associated with anisolation path by application of the mathematical function and storingthe estimated value in the storage medium.
 14. The method of claim 13,further comprising: comparing the estimated values of capacitance with arange of acceptable values and communicating that the estimated value ofthe at least first capacitance is outside a range of acceptable values.15. The method of claim 13, wherein the power source is a battery andthe at least first reference point in the electrical system is aterminal of the battery.
 16. The method of claim 15, wherein themeasured voltage values are measurements of a varying voltage within theelectrical system while the electrical system is operating andmeasurements of a voltage signal source while the electrical system isidle.
 17. The method of claim 16, wherein the mathematical functionstored in the storage medium is a least square estimator which producesa least squared error estimate.
 18. The method of claim 17, wherein theleast squared error estimate is performed over a predetermined number ofvoltage measurements and corresponding voltage predictions, therebyminimizing a deviation between the measured voltage values and theestimated voltage values, and thereby producing a corresponding numberof present value estimates and associated uncertainties for the presentvalue estimates.
 19. The method of claim 18, wherein the method stepsare performed iteratively.
 20. The method of claim 19, wherein thepresent value estimates are expressed as a vector and the associateduncertainties are expressed as a covariance matrix for the vector. 21.The method of claim 20, further comprising a stochastic filter, whereinthe extracted estimated values are fed to the filter and the filtermaintains the most likely present value estimates and associateduncertainties for the present value estimates.
 22. The method of claim21, wherein the stochastic filter is a Kalman filter.
 23. The method ofclaim 22, further comprising: receiving as inputs to the Kalman filter aset of previous present value estimates and associated uncertainties;receiving as inputs to the Kalman filter a set of estimated values,including the estimated value of the resistance change and the estimatedvalue of the capacitance change; outputting a new set of values for themost likely present value estimates and associated uncertainties byapplication of the filter; and updating the present value estimates andassociated uncertainties stored in the storage medium.
 24. The method ofclaim 23, wherein the method steps are performed iteratively.
 25. Anapparatus for estimating unknown values of isolation impedance in anisolated ground (IT) electrical power system, comprising: a power sourcehaving a positive terminal and a negative terminal, said terminalsconnected in circuit to at least one additional electrical component andisolated from a chassis ground within the electrical system; wherein theelectrical system contains an isolation impedance between each of theterminals and the chassis ground; a storage medium; means measuring aninitial value and a subsequent different value of a voltage between thechassis ground and a first reference point and between a secondreference point and a third reference point in the electrical system;means storing the measured initial values and the subsequent differentvalues in the storage medium; a mathematical function stored in thestorage medium, whereby application of the mathematical functionextracts estimated values of isolation impedances associated with thevoltage measurements by using a model of the electrical system andminimizing an error function.
 26. The apparatus of claim 25, furthercomprising: wherein the electrical system contains at least onecapacitance between each of the terminals and the chassis ground, andwherein the mathematical function extracts an estimated value of thecapacitance associated with the voltage measurement.
 27. The apparatusof claim 25, wherein the power source is a battery.
 28. The apparatus ofclaim 25, wherein the power source is a power conversion system.
 29. Anapparatus for estimating a change in values of isolation impedance in anisolated ground (IT) electrical power system, comprising: a power sourcehaving a positive terminal and a negative terminal, said terminalsconnected in circuit to at least one additional electrical component andisolated from a chassis ground within the electrical system; wherein theelectrical system contains an isolation impedance between each of theterminals and the chassis ground; a storage medium; means measuring aninitial value and a subsequent different value of a voltage between thechassis ground and a first reference point and between a secondreference point and a third reference point in the electrical system;means storing the measured initial values and the subsequent differentvalues in the storage medium; a mathematical function stored in thestorage medium, whereby application of the mathematical functionextracts an estimated change in values of isolation impedancesassociated with the voltage measurements by using a model of theelectrical system and minimizing an error function.
 30. A method toestimate a change in values of isolation impedance in an isolated ground(IT) electrical system comprising a power source and a load, the methodcomprising: modeling a first isolation path between a first referencepoint and a second reference point and modeling a second isolation pathbetween a third reference point and a fourth reference point, therebycreating a theoretical model of the isolated ground electrical system;at a time when power from the power source is being dissipated in theload, measuring an initial value of a voltage between the firstreference point and the second reference point and storing the measuredinitial value in a storage medium; at a time when power from the powersource is being dissipated in the load, measuring an initial value of avoltage between the third reference point and the fourth reference pointand storing the measured initial value in the storage medium; at a timewhen power from the power source is being dissipated in the load,measuring a subsequent different value of the voltage between the firstreference point and the second reference point and storing the measuredsubsequent value in the storage medium; at a time when power from thepower source is being dissipated in the load, measuring a subsequentvalue of the voltage between the third reference point and the fourthreference point and storing the measured subsequent value in the storagemedium; entering the measured initial values of the voltages, themeasured subsequent values of the voltages and an elapsed amount of timebetween the initial measurements and the subsequent measurements into amathematical function stored in the storage medium; wherein themathematical function minimizes the discrepancy between the measuredinitial values of the voltages, the measured subsequent values of thevoltages and the modeled theoretical values by adjusting values ofmodeled isolation impedances associated with the isolation paths in theelectrical system; extracting estimated values of isolation impedancesassociated with the isolation paths in the electrical system byapplication of the mathematical function; and storing the estimatedvalues in the storage medium.
 31. The method of claim 30, wherein thesecond reference point is a chassis ground of the electrical system. 32.The method of claim 31, wherein the fourth reference point is thechassis ground of the electrical system.
 33. The method of claim 30,further comprising: comparing the estimated values of isolationresistance with a range of acceptable values and communicating that theestimated value of resistance for an isolation path is outside the rangeof acceptable values.
 34. The method of claim 30, further comprising:communicating an amount of estimated energy stored in the isolationimpedances.
 35. The method of claim 30, wherein the power source is abattery and wherein the first reference point and the third referencepoint are positive and negative terminals of the battery.
 36. The methodof claim 30, wherein the power source is a supercapacitor.
 37. Themethod of claim 30, wherein the power source is a DC charger.
 38. Themethod of claim 37, further comprising: identifying a minimum resistancepath from the estimated values of isolation resistance.
 39. The methodof claim 38, further comprising: communicating a value of resistance forthe minimum resistance path in the electrical system.
 40. The method ofclaim 38, further comprising: associating the minimum resistance pathwith one of the power source terminals.
 41. The method of claim 30,wherein the theoretical model of the electrical system is an equivalentcircuit model.
 42. The method of claim 30, further comprising:extracting an estimated value of at least a first capacitance associatedwith an isolation path by application of the mathematical function andstoring the estimated value in the storage medium.
 43. The method ofclaim 42, further comprising: comparing the estimated values ofcapacitance with a range of acceptable values and communicating that theestimated value of the at least first capacitance is outside a range ofacceptable values.
 44. The method of claim 42, wherein the power sourceis a battery and the at least first reference point in the electricalsystem is a terminal of the battery.
 45. The method of claim 44, whereinthe measured voltage values are measurements of a varying voltage withinthe electrical system while the electrical system is operating andmeasurements of a voltage signal source while the electrical system isidle.
 46. The method of claim 45, wherein the mathematical functionstored in the storage medium is a least square estimator which producesa least squared error estimate.
 47. The method of claim 46, wherein theleast squared error estimate is performed over a predetermined number ofvoltage measurements and corresponding voltage predictions, therebyminimizing a deviation between the measured voltage values and theestimated voltage values, and thereby producing a corresponding numberof present value estimates and associated uncertainties for the presentvalue estimates.
 48. The method of claim 47, wherein the method stepsare performed iteratively.
 49. The method of claim 48, wherein thepresent value estimates are expressed as a vector and the associateduncertainties are expressed as a covariance matrix for the vector. 50.The method of claim 49, further comprising a stochastic filter, whereinthe extracted estimated values are fed to the filter and the filtermaintains the most likely present value estimates and associateduncertainties for the present value estimates.
 51. The method of claim50, wherein the stochastic filter is a Kalman filter.
 52. The method ofclaim 51, further comprising: receiving as inputs to the Kalman filter aset of previous present value estimates and associated uncertainties;receiving as inputs to the Kalman filter a set of estimated values,including the estimated value of the resistance change and the estimatedvalue of the capacitance change; outputting a new set of values for themost likely present value estimates and associated uncertainties byapplication of the filter; and updating the present value estimates andassociated uncertainties stored in the storage medium.
 53. The method ofclaim 52, wherein the method steps are performed iteratively.